SCADA-Based Reliability Evaluation

Kelmarsh Wind Farm - 12.3 MW

Kelmarsh Wind Farm

Project Overview

“Kelmarsh comprises six 2.05MW Senvion MM92 turbines. The Project was acquired from EON in December 2014 and was constructed in joint venture with Santander using balance sheet finance. Construction was completed in April 2016. It is now owned by Cubico Investments.”

• https://www.blue-energyco.com/our-projects/kelmarsh/

(a) Kelmarsh Wind Farm

(b) Senvion MM92 turbine

Figure 1: Kelmarsh Wind Farm is located near Haselbach, Northamptonshire, UK.

Events Catalogue and Status

IEC category	Stop	Warning	Informational	Curtailment	Communication
Requested Shutdown	77	0	0	0	0
None	21	2320	168	0	744
Out of Environmental Specification	93	0	90500	0	0
Scheduled Maintenance	818	0	0	0	0
Forced outage	892	403	0	0	0
Partial Performance	0	9	0	37	0
Full Performance	0	1461	227877	0	0
Technical Standby	3094	0	56248	0	0
Out of Electrical Specification	371	0	0	0	0
Note: Only "Forced outage" events with status "Stop" are considered for the evaluation, i.e., 892 events.

Reliability Parameters

Six Wind Turbines - Model Senvion MM92
Reliability Evaluation (2016 - 2022)
	Turbine	Forced Outages			*Ready [h]		Out-of-Service [h]		Probabilities
		Total	Monthly	λ [h⁻¹]	Uptime	MTTF	Downtime	MTTR	FOR (P0)	A (P1)
2016
T01		32		0.00379	7,951.52	248.49	501.01	15.66	0.05927	0.94073
T02		53		0.00639	8,136.62	156.47	153.18	2.89	0.01814	0.98186
T03		30		0.00368	7,965.13	265.50	178.92	5.96	0.02197	0.97803
T04		18		0.00226	7,907.14	439.29	41.90	2.33	0.00527	0.99473
T05		17		0.00207	7,775.08	457.36	441.71	25.98	0.05376	0.94624
T06		29		0.00367	7,723.99	275.86	183.64	6.33	0.02244	0.97756
2017
T01		24		0.00283	8,429.53	351.23	42.66	1.78	0.00504	0.99496
T02		17		0.00201	8,453.93	497.29	7.28	0.43	0.00086	0.99914
T03		9		0.00120	7,473.43	830.38	3.73	0.41	0.00050	0.99950
T04		21		0.00247	8,500.80	404.80	5.85	0.28	0.00069	0.99931
T05		14		0.00165	8,501.42	607.24	6.07	0.43	0.00071	0.99929
T06		37		0.00430	8,487.32	229.39	119.79	3.24	0.01392	0.98608
2018
T01		12		0.00138	8,705.76	725.48	3.84	0.32	0.00044	0.99956
T02		19		0.00218	8,696.98	457.74	12.56	0.66	0.00144	0.99856
T03		24		0.00276	8,699.04	362.46	10.45	0.44	0.00120	0.99880
T04		11		0.00126	8,699.60	790.87	9.87	0.90	0.00113	0.99887
T05		11		0.00126	8,665.10	787.74	44.86	4.08	0.00515	0.99485
T06		19		0.00219	8,656.02	455.58	6.71	0.35	0.00077	0.99923
2019
T01		15		0.00201	7,452.84	496.86	8.63	0.58	0.00116	0.99884
T02		17		0.00216	7,837.26	461.02	23.18	1.36	0.00295	0.99705
T03		10		0.00148	6,735.20	673.52	21.06	2.11	0.00312	0.99688
T04		17		0.00234	7,266.50	427.44	8.20	0.48	0.00113	0.99887
T05		8		0.00110	7,268.16	908.52	7.66	0.96	0.00105	0.99895
T06		9		0.00114	7,811.74	867.97	54.96	6.11	0.00699	0.99301
2020
T01		21		0.00268	7,799.24	371.39	41.31	1.97	0.00527	0.99473
T02		25		0.00319	7,821.99	312.88	18.92	0.76	0.00241	0.99759
T03		14		0.00179	7,763.12	554.51	75.25	5.37	0.00960	0.99040
T04		30		0.00383	7,774.38	259.15	66.99	2.23	0.00854	0.99146
T05		16		0.00204	7,814.71	488.42	25.69	1.61	0.00328	0.99672
T06		24		0.00306	7,824.05	326.00	14.88	0.62	0.00190	0.99810
2021
T01		24		0.00301	7,861.40	327.56	114.53	4.77	0.01436	0.98564
T02		14		0.00176	7,973.40	569.53	2.71	0.19	0.00034	0.99966
T03		12		0.00150	7,973.98	664.50	1.95	0.16	0.00024	0.99976
T04		10		0.00125	7,974.63	797.46	1.15	0.12	0.00014	0.99986
T05		27		0.00339	7,681.87	284.51	294.06	10.89	0.03687	0.96313
T06		13		0.00155	8,258.67	635.28	110.83	8.53	0.01324	0.98676
2022
T01		85		0.00980	8,653.87	101.81	21.94	0.26	0.00253	0.99747
T02		33		0.00389	8,428.90	255.42	59.77	1.81	0.00704	0.99296
T03		7		0.00082	8,484.88	1,212.13	3.71	0.53	0.00044	0.99956
T04		9		0.00106	8,426.84	936.32	61.75	6.86	0.00727	0.99273
T05		34		0.00392	8,671.34	255.04	8.37	0.25	0.00096	0.99904
T06		18		0.00212	8,059.58	447.75	428.91	23.83	0.05053	0.94947
* Forced Outages (IEC) only. Yearly evaluation period -> Censored uptime (TTF) data around year change.

Time / State Diagrams

2016

2017

2018

2019

2020

2021

2022

Histogram of Failure Causes

Total

Per Wind Turbine

References

Iannone, Richard, and Michael Chow. n.d. “great-tables: Make awesome display tables using Python.” https://github.com/posit-dev/great-tables.

Inc., Plotly Technologies. 2015. “Collaborative Data Science.” Montreal, QC: Plotly Technologies Inc. 2015. https://plot.ly.

Mühleisen, Hannes, Mark Raasveldt, et al. 2025. “DuckDB: An Embeddable Analytical Database.” https://duckdb.org.

Plumley, Charlie. 2022. “Kelmarsh Wind Farm Data (0.1.0) [Data Set].” Zenodo. https://zenodo.org/records/8252025.

Vink, Ritchie, and contributors. 2025. “Polars: Fast Multi-Threaded DataFrame Library in Rust and Python.” https://www.pola.rs/.